Service qualities offered to the bicycle through movement at signalized intersections under heterogeneous traffic conditions have been modeled using attributes collected from 35 intersection approaches. Perceived satisfactions of 160 users were assessed and seven major attributes contributing to bicycle services were identified. A highly reliable model (R2 = 0.86) was developed using step-wise regression analysis. Sensitivity analysis carried out on modelled variables reported that, main-street traffic volume (38%), width of main-street (17.6%), pavement conditions (15.9%) and average stopped time delay (15.2%) are by far the most important variables. Affinity Propagation clustering was used to define ranges of service categories (A-F).